Taking the mean of a matrix with NaN's in Matlab [duplicate] - matlab

This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
Dealing with NaN’s in matlab functions
Is there a one line command that allows you to take the elementwise average of a matrix (ignoring NaN's) in Matlab? For example,
>> A = [1 0 NaN; 0 3 4; 0 NaN 2]
A =
1 0 NaN
0 3 4
0 NaN 2
So the mean(A) should equal (1+3+2+4+0+0+0)/7 = 1.4286
Also, I don't have access to the stats toolbox so I cannot use nanmean()

You can use isnan() to filter out the unwanted elements:
mean(A(~isnan(A)))

nanmean
Performs just like mean, but ignoring nans.
For example:
>> A = [1 0 NaN; 0 3 4; 0 NaN 2]
A =
1 0 NaN
0 3 4
0 NaN 2
>> nanmean(A)
ans =
0.333333333333333 1.5 3
>> nanmean(A,2)
ans =
0.5
2.33333333333333
1
>> nanmean(A(:))
ans =
1.42857142857143

Related

Octave: A(~isnan(A)) results vector containing NaNs?

May be I don't get a basic thing, but I recently discovered this behaviour, and by now I don't understand what's happening:
A = [3 NaN .12 NaN NaN 9]
A =
3 NaN 0.12 NaN NaN 9
>> nansA = isnan(A)
nansA =
0 1 0 1 1 0
>> nnansA = ~isnan(A)
nnansA =
1 0 1 0 0 1
>> nnansA1 = ~isnan(A(1:end))
nnansA1 =
1 0 1 0 0 1
>> nnansA2 = ~isnan(A(2:end))
nnansA2 =
0 1 0 0 1
>> AnnansA1 = A(~isnan(A(1:end)))
AnnansA1 =
3 0.12 9
>> **AnnansA2 = A(~isnan(A(2:end)))
AnnansA2 =
NaN NaN
What is happening here?
Does this happen in Matlab too?
I would expect something like ... AnnansA2 = 0.12 9
What is happening here is that you're indexing A with a logical array of a different size and expect the indexing to not start at the beginning.
Let's deconstruct, from the inside:
>> A = [3 NaN .12 NaN NaN 9]
A =
3.0000 NaN 0.1200 NaN NaN 9.0000
>> # B a new array, with 5 elements (A had 6 elements)
>> B = A(2:end)
B =
NaN 0.1200 NaN NaN 9.0000
>> # mask is a logical array with 5 elements, like B, and not 6, like A.
>> # mask knows nothing about A or B. It simply "selects" (indexes) the
>> # 1st, 3rd, and 4th element of any array.
>> mask = isnan (B)
mask =
1 0 1 1 0
>> # Invert the mask, now "selects" the 2nd and 5th element of any array.
>> not_mask = ! mask
not_mask =
0 1 0 0 1
>> # Return the 2nd and 5th element of A.
>> A(not_mask)
ans =
NaN NaN
I think you're surprised by the behaviour because you expect that A(2:end) "remembers" that it comes from A to index the right "region" of A. This does not happen, it's just a logical array that "remembers" nothing from which array it came (and often used to index different arrays).
As a side note, and answering one of your questions, Matlab behaviour is the same as Octave.
Anyway, what you're doing looks a bit odd, maybe do this instead:
A(! isnan (A))(2:end)
You're off by one.
You need to do AnnansA2 = A(~isnan(A(1:end)))
If you want to return only the last two non-nans, index the result like;
ananIdxs = ~isnan(A)
AnnansA2 = A(ananIdxs(2:end))

How can I remove NaN values from a dataset? [duplicate]

This question already has answers here:
Is there any general way to remove NaNs from a matrix?
(5 answers)
Closed 6 years ago.
New to MATLAB, any help with this would be appreciated.
I have a dataset that is 1000 elements in 1 column, and most of the elements are numbers but some are NaN's. Is there a way I can, 1. Find them, and 2. Remove them and put them in a variable (or just remove them)?
Would I have to do this the reverse way and find and remove the non-NaN's (the numbers) and store them in a variable?
Use logical indexing to extract the elements that are not NaN and then store them anywhere you like. Here's how it works. If x is your column vector containing NaN, y = ~isnan(x) will give a logical vector y such that |y|=|x| and y(i) is 1 iff x(1) is not NaN. You can use this logical vector to extract non NaN elements:
x = [1 2 3 NaN 5 6 NaN NaN 9];
y = ~isnan(x); % now y is [1 1 1 0 1 1 0 0 1]
x = x(y) % now x is [1 2 3 5 6 9]
Logical indexing is powerful and efficient. You could also say:
x = [1 2 3 NaN 5 6 NaN NaN 9];
x(isnan(x)) = -1 % now x is [1 2 3 -1 5 6 -1 -1 9]
For more information on logical indexing see the official Matlab documentation here.
A option equivalent to #sadeghmir's answer:
x = [1 2 3 NaN 5 6 NaN NaN 9];
x(x==NaN)=[];
>x
1 2 3 5 6 9

Number of Non-NaN Rows in a 3D Matrix MATLAB

I have a 3D matrix with NaN padded to obtain equal number of rows in each 2D matrix i.e each (:,:,ind). Now i need to find the number of actual non-NaN rows in each (:,:,ind).
A simple example of what I need:
% Input:
A(:,:,1) = [ 1 1;
2 2;
NaN NaN];
A(:,:,2) = [ 2 2;
NaN NaN;
NaN NaN];
% Function call:
B = callingfunction(A);
% Output:
B = [2 1] % Number of Non-NaN rows in each 2D Matrix
Approach #1
B = squeeze(sum(all(~isnan(A),2),1))
Here's the build-up process to get a hang of it -
Start>>> Given A:
>> A
A(:,:,1) =
1 1
2 2
NaN NaN
A(:,:,2) =
2 2
NaN NaN
NaN NaN
1) Detect all non-NaN positions:
>> ~isnan(A)
ans(:,:,1) =
1 1
1 1
0 0
ans(:,:,2) =
1 1
0 0
0 0
2) Find rows with all non-Nan elements:
>> all(~isnan(A),2)
ans(:,:,1) =
1
1
0
ans(:,:,2) =
1
0
0
3) Sum up the number of all such rows:
>> sum(all(~isnan(A),2),1)
ans(:,:,1) =
2
ans(:,:,2) =
1
4) Get the result as a 1D array:
>> squeeze(sum(all(~isnan(A),2),1))
ans =
2
1
Approach #2
B = squeeze(sum(~any(isnan(A),2),1))
Use the same break-up-my-code-into-pieces process as listed earlier here and in all your future MATLAB codes and all past MATLAB codes that didn't make sense to do so now!

Getting row and column numbers of valid elements in a matrix

I have a 3x3 matrix, populated with NaN and values of a variable:
NaN 7 NaN
5 NaN 0
NaN NaN 4
matrix = [NaN 7 NaN; 5 NaN 0; NaN NaN 4]
I would like to get the row and column numbers of non-NaN cells and put them in a matrix together with the value of the variable. That is, I would like to obtain the following matrix:
row col value
1 2 7
2 1 5
2 3 0
3 3 4
want = [1 2 7; 2 1 5; 2 3 0; 3 3 4]
Any help would be highly appreciated.
This can be done without loops:
[jj, ii, kk] = find((~isnan(matrix).*(reshape(1:numel(matrix), size(matrix)))).');
result = [ii jj matrix(kk)];
The trick is to multiply ~isnan(matrix) by a matrix of indices so that the third output of find gives the linear index of non-NaN entries. The transpose is needed to have the same order as in the question.
The following should work!
[p,q]=find(~isnan(matrix)) % Loops through matrix to find indices
want = zeros(numel(p),3) % three columns you need with same number of rows as p
for i=1:numel(p)
want[i,:] = [p(i) q(i) matrix(p(i), matrix(i))]
end
Should give you the correct result which is:
2 1 5
1 2 7
2 3 0
3 3 4
If you don't mind the ordering of the rows, you can use a simplified version of Luis Mendo's answer:
[row, col] = find(~isnan(matrix));
result = [row(:), col(:), matrix(~isnan(matrix))];
Which will result in:
2 1 5
1 2 7
2 3 0
3 3 4

Matlab: How to Insert 'NaN' in every n-rows

This is just a very simple example to show my problem.
a=ones(5)
How can i insert NaN after every two rows like:
I know the way to do this simple example is:
b(:,1:5)=NaN
[a(1:2,:);b;a(3:4,:);b;a(end,:)]
But the problem is if the martrix is 60000-by-200 (may be more larger), so how can i insert 'NaN' after every two rows.
Thanks so much.
a = ones(5); %// example data
n = 2; %// number of rows
N = floor(size(a,1)*(1+1/n)); %// final number of rows
ind = mod(1:N, n+1) ~= 0; %// logical index for non-NaN rows
b = NaN(N,size(a,2)); %// initiallize result to NaN
b(ind,:) = a; %// fill in non-NaN rows
I can't think of an easy, one-line type solution. It can be done in a pretty tight loop though.
a = ones(5);
a_with_nans = nan(floor(size(a,1)*(3/2)), size(a,2)); %Start with all nans in a larger matrix
for ix = 1:2:size(a,1)
a_with_nans(ix*3/2-(1/2),:) = a(ix,:);
if ix+1<=size(a,1)
a_with_nans(ix*3/2-(1/2)+1,:) = a(ix+1,:);
end
end
Then:
a_with_nans =
1 1 1 1 1
1 1 1 1 1
NaN NaN NaN NaN NaN
1 1 1 1 1
1 1 1 1 1
NaN NaN NaN NaN NaN
1 1 1 1 1
You can do it like this:
>> a= [ 1 2 3 4 5 6 7 8 9]
a =
1 2 3 4 5 6 7 8 9
>> b = nan(floor(length(a)/2),1)'
b =
NaN NaN NaN NaN
>> a_new = zeros(1, length(a)+length(b))
a_new =
0 0 0 0 0 0 0 0 0 0 0 0 0
>> b_i = 3:2:length(a)
b_i =
3 5 7 9
>> a_new(b_i+(0:length(b_i)-1)) = b
a_new =
0 0 NaN 0 0 NaN 0 0 NaN 0 0 NaN 0
>> a_new(~isnan(a_new))=a
a_new =
1 2 NaN 3 4 NaN 5 6 NaN 7 8 NaN 9